/*-
 *
 *  * Copyright 2015 Skymind,Inc.
 *  *
 *  *    Licensed under the Apache License, Version 2.0 (the "License");
 *  *    you may not use this file except in compliance with the License.
 *  *    You may obtain a copy of the License at
 *  *
 *  *        http://www.apache.org/licenses/LICENSE-2.0
 *  *
 *  *    Unless required by applicable law or agreed to in writing, software
 *  *    distributed under the License is distributed on an "AS IS" BASIS,
 *  *    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 *  *    See the License for the specific language governing permissions and
 *  *    limitations under the License.
 *
 */

package org.deeplearning4j.clustering.strategy;

import org.deeplearning4j.clustering.condition.ClusteringAlgorithmCondition;
import org.deeplearning4j.clustering.condition.ConvergenceCondition;
import org.deeplearning4j.clustering.condition.FixedIterationCountCondition;
import org.deeplearning4j.clustering.iteration.IterationHistory;
import org.deeplearning4j.clustering.optimisation.ClusteringOptimization;
import org.deeplearning4j.clustering.optimisation.ClusteringOptimizationType;

public class OptimisationStrategy extends BaseClusteringStrategy {
    public static int defaultIterationCount = 100;

    private ClusteringOptimization clusteringOptimisation;
    private ClusteringAlgorithmCondition clusteringOptimisationApplicationCondition;

    protected OptimisationStrategy() {
        super();
    }

    protected OptimisationStrategy(int initialClusterCount, String distanceFunction) {
        super(ClusteringStrategyType.OPTIMIZATION, initialClusterCount, distanceFunction, false);
    }

    public static OptimisationStrategy setup(int initialClusterCount, String distanceFunction) {
        return new OptimisationStrategy(initialClusterCount, distanceFunction);
    }

    public OptimisationStrategy optimize(ClusteringOptimizationType type, double value) {
        clusteringOptimisation = new ClusteringOptimization(type, value);
        return this;
    }

    public OptimisationStrategy optimizeWhenIterationCountMultipleOf(int value) {
        clusteringOptimisationApplicationCondition = FixedIterationCountCondition.iterationCountGreaterThan(value);
        return this;
    }

    public OptimisationStrategy optimizeWhenPointDistributionVariationRateLessThan(double rate) {
        clusteringOptimisationApplicationCondition = ConvergenceCondition.distributionVariationRateLessThan(rate);
        return this;
    }


    public double getClusteringOptimizationValue() {
        return clusteringOptimisation.getValue();
    }

    public boolean isClusteringOptimizationType(ClusteringOptimizationType type) {
        return clusteringOptimisation != null && clusteringOptimisation.getType().equals(type);
    }

    public boolean isOptimizationDefined() {
        return clusteringOptimisation != null;
    }

    public boolean isOptimizationApplicableNow(IterationHistory iterationHistory) {
        return clusteringOptimisationApplicationCondition != null
                        && clusteringOptimisationApplicationCondition.isSatisfied(iterationHistory);
    }

}
